Undesirable factors in stochastic cross-efficiency evaluation

Subject Areas : International Journal of Data Envelopment Analysis

Mehdi Khodadadipour ¹ , Abdollah Hadi-Vencheh ² , Mohhamad Reza Behzadi ³ , Mohsen Rostamy-Malkhalifeh ⁴

1 - Department of Statistics , Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - IAU, Isfahan Branch
3 - IAU, Science and Research Branch
4 - Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran

Received: 2020-03-07 Accepted : 2020-06-17 Published : 2020-07-01

Keywords: expected ranking criterion, stochastic cross-efficiency evaluation, ranking priority, Undesirable Multiple Form (UMF),

Abstract :

Cross-efficiency evaluation in Data envelopment analysis (DEA) has been accepted as a useful tool for performance evaluation and ranking of decision making units. In this paper using Undesirable Multiple Form (UMF) model with specific risk of α, a new stochastic model called Expected Ranking Criterion is introduced using statistical techniques for efficiency evaluation decision making units (DMU). Another issue in applying cross-efficiency DEA models is considering stochastic in input and output variables. Also, the non-uniqueness of optimal weights in this evaluation has reduced the usefulness of this powerful method. As a result, it is recommended that secondary goals be introduced in cross-efficiency evaluation. In this paper, the cross-efficiency model is modified to deal with stochastic data by applying chance-constrained approach.